False‐positive stress testing: Does endothelial vascular dysfunction contribute to ST‐segment depression in women? A pilot study
Bibliographic record
Abstract
BACKGROUND: The utility of exercise-induced ST-segment depression for diagnosing ischemic heart disease (IHD) in women is unclear. HYPOTHESIS: Based on evidence that IHD pathophysiology in women involves coronary vascular dysfunction, we hypothesized that coronary vascular dysfunction contributes to exercise electrocardiography (Ex-ECG) ST-depression in the absence of obstructive coronary artery disease, so-called false positive results. We tested our hypothesis in a pilot study evaluating the relationship between peripheral vascular endothelial function and Ex-ECG. METHODS: Twenty-nine asymptomatic women without cardiac risk factors underwent maximal Bruce protocol exercise treadmill testing and peripheral endothelial function assessment using peripheral arterial tonometry (Itamar EndoPAT 2000) to measure reactive hyperemia index (RHI). The relationship between RHI and Ex-ECG ST-segment depression was evaluated using logistic regression and differences in subgroups using 2-tailed t tests. RESULTS: , and RHI 2.51 ± 0.66. Three women (10%) had RHI <1.68, consistent with abnormal peripheral endothelial function, whereas 18 women (62%) met criteria for positive Ex-ECG based on ST-segment depression in contiguous leads. Women with and without ST-segment depression had similar baseline and exercise vital signs, metabolic equivalents achieved, and RHI (all P > 0.05). RHI did not predict ST-segment depression. CONCLUSIONS: Our pilot study demonstrates high prevalence of exercise-induced ST-segment depression in asymptomatic, middle-aged, overweight women. Peripheral vascular endothelial dysfunction did not predict Ex-ECG ST-segment depression. Further work is needed to investigate the utility of vascular endothelial testing and Ex-ECG for IHD diagnostic and management purposes in women.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".